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Record W3013951672 · doi:10.1080/09540121.2020.1739203

AIDSImpact special issue – broadening the lens: recommendations from rehabilitation in chronic disease to advance healthy ageing with HIV

2020· article· en· W3013951672 on OpenAlexaffabout
Kelly K. O’Brien, Darren A. Brown, Colin Corbett, Nick Flanagan, Patricia Solomon, Jaime H. Vera, Rachel Aubry, Richard Harding

Bibliographic record

VenueAIDS Care · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsMcMaster UniversityToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsRehabilitationMedicineDiseaseStigma (botany)Mental healthHealthy ageingHuman immunodeficiency virus (HIV)GerontologyAgeingFamily medicinePhysical therapyPsychiatryPathology

Abstract

fetched live from OpenAlex

People living with HIV are ageing with a combination of physical, mental and social health challenges, known as disability. Although rehabilitation can address disability, the field is still emerging. Our aim was to identify similar disability experiences across complex chronic conditions and establish recommendations for future rehabilitation research and practice to advance healthy ageing with HIV. We conducted a consultation with 77 stakeholders from the United Kingdom, Canada, and Ireland with expertise in the fields of rehabilitation and HIV, cancer, cardiovascular disease, renal disease, or chronic obstructive pulmonary disease who attended a one-day symposium. We used facilitated discussions to identify how rehabilitation issues in complex chronic disease translate to people ageing with HIV, and prioritised recommendations for future practice and research. Disability issues experienced across HIV and other complex chronic diseases included: (i) frailty, (ii) uncertainty and worrying about the future ageing with complex chronic disease, (iii) mental health, (iv) pain, and (v) stigma. We highlight six recommendations for clinical practice and research to advance healthy ageing with HIV. Opportunities for cross-collaboration exist with other more established areas of chronic disease management and rehabilitation. Recommendations can be used to inform future HIV clinical practice and research in this emerging field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.330
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

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